Non-uniqueness of stationary measures for stochastic systems with almost surely invariant manifolds
Jacob Bedrossian, Alex Blumenthal, Sam Punshon-Smith

TL;DR
This paper presents a general framework for proving the existence of multiple stationary measures in stochastic dynamical systems with invariant manifolds, demonstrated through the Lorenz 96 model with degenerate forcing.
Contribution
It introduces a novel theoretical approach to establish non-uniqueness of stationary measures using Lyapunov exponents and applies it to complex high-dimensional systems.
Findings
Multiple stationary measures exist for the Lorenz 96 model under certain conditions.
A bifurcation occurs leading to exactly two stationary measures as damping decreases.
Computer-assisted methods verify hypoellipticity and irreducibility conditions.
Abstract
We develop a general framework for establishing non-uniqueness of stationary measures for stochastically forced dynamical systems possessing an almost surely invariant submanifold. Our main abstract result provides sufficient conditions for the existence of multiple stationary measures on compact manifolds, though the underlying methodology extends to non-compact settings. The key insight is to construct additional stationary measures by exploiting the linear instability of the invariant submanifold, as quantified by a positive transverse Lyapunov exponent. To demonstrate the practical applicability of our framework, we apply it to the Lorenz 96 model with degenerate stochastic forcing, which serves as an example of both non-compact and high-dimensional dynamics. We prove that as the damping parameter becomes sufficiently small, the unique stationary measure bifurcates, giving rise to…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Code & Models
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsStability and Controllability of Differential Equations · Mathematical Dynamics and Fractals · Chaos control and synchronization
